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	<title>Rohan Kamat &#8211; Noise</title>
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		<title>Securing client confidentiality at scale: Automated data discovery and governed analytics for legal workloads</title>
		<link>https://noise.getoto.net/2026/05/13/securing-client-confidentiality-at-scale-automated-data-discovery-and-governed-analytics-for-legal-workloads/</link>
		
		<dc:creator><![CDATA[Rohan Kamat]]></dc:creator>
		<pubDate>Wed, 13 May 2026 15:57:14 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Macie]]></category>
		<category><![CDATA[Amazon Quick Suite]]></category>
		<category><![CDATA[Amazon Simple Notification Service (SNS)]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[AWS Security Hub]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show you a reference architecture that automates sensitive data discovery across legal document repositories on Amazon Web Services (AWS), demonstrate how to capture structured findings as a compliance dataset, and guide you through building a governed analytics workspace that maintains your security boundaries. You walk away with a practical model for building security and analytics into the same lifecycle, without moving documents outside their system of record.]]></description>
		
		
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